Mobile health is gaining increasing importance for society and the quest for new power efficient devices sampling biosignals is becoming critical. We discuss a new scheme called Variable PulseWidth Finite Rate of Innovation (VPW-FRI) to model and compress ECG signals. This technique generalizes classical FRI estimation to enable the use of a sum of asymmetric Cauchy-based pulses for modeling electrocardiogram (ECG) signals. We experimentally show that VPW-FRI indeed models ECG signals with increased accuracy compared to current standards. In addition, we study the compression efficiency of the method: compared with various widely used compression schemes, we showcase improvements in terms of compression efficiency as well as sampling rate.